Lithography has a broad range of industrial applications, including the manufacture of semiconductors, flat-panel displays, micromachines, and disk heads.
The lithographic process allows for a mask or reticle pattern to be transferred via spatially modulated light (the aerial image) to a photoresist film on a substrate. Those segments of the absorbed aerial image, whose energy exceeds a threshold energy of chemical bonds in the photo-active component (PAC) of the photoresist material, create a latent image in the photoresist. In some photoresist systems the latent image is formed directly by the PAC; in others (so-called acid catalyzed photoresists), the photo-chemical interaction first generates acids which react with other photoresist components during a post-exposure bake to form the latent image. In either case, the latent image marks the volume of photoresist material that either is removed during the development process (in the case of positive photoresist) or remains after development (in the case of negative photoresist) to create a three-dimensional pattern in the photoresist film.
The principal determinant of the photoresist image is the surface on which the exposure energy equals the photoresist threshold energy in the photoresist film. "Exposure" and "focus" are the variables that control the shape of this surface. Exposure, set by the illumination time and intensity, determines the average energy of the aerial image per unit area. Local variations in exposure can be caused by variations in substrate reflectivity and topography. Focus, set by the position of the photoresist film relative to the focal plane of the imaging system, determines the decrease in modulation relative to the in-focus image. Local variations in focus can be caused by variations in substrate film thickness and topography.
Generally, because of the variations in exposure and focus, patterns developed by lithographic processes must be continually monitored or measured to determine if the dimensions of the patterns are within acceptable range. The importance of such monitoring increases considerably as the resolution limit, which is usually defined as minimum feature size resolvable, of the lithographic process is approached. The patterns being developed in semiconductor technology are generally in the shape of lines both straight and with bends, having a length dimension equal to and multiple times the width dimension. The width dimension, which by definition is the smaller dimension, is of the order of 0.1 micron to greater than 1 micron in many of the current leading semiconductor technology. Because the width dimension is the minimum dimension of the patterns, it is the width dimension that challenges the resolution limits of the lithographic process. In this regard, because width is the minimum and most challenging dimension to develop, it is the width dimension that is conventionally monitored to assess performance of the lithographic process. The term "bias" is used to describe the change in a dimension of a feature from its nominal value. Usually the bias of interest is the change in the smallest of the dimensions of a given feature. Further, the word "bias" is invariably used in conjunction with a process such as resist imaging, etching, developing etc. and described by terms such as image bias, etch bias, print bias etc.
Monitoring of pattern features and measurement of its dimensions (metrology) is typically performed using either a scanning electron microscope (SEM) or an optical tool. SEM metrology has very high resolving power and is capable of resolving features of the order of 0.1 micron. Unfortunately, SEM metrology is expensive to implement, relatively slow in operation and difficult to automate. Although optical metrology overcomes the above drawbacks associated with SEM metrology, optical metrology systems are unable to resolve adequately for measurement of feature dimensions of less than about 1 micron. Thus, optical metrology systems are unable to resolve state-of-the-art circuit line width dimensions, which are currently on the order of less than 1 micron.
Accordingly, there is still a need for a method of monitoring pattern features with dimensions on the order of less than 1 micron, and which is inexpensive to implement, fast in operation and simple to automate.